_base_ = [
    '../_base_/models/cascade_rcnn_r50_fpn.py',
    '../_base_/datasets/coco_detection.py',
    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]


# optimizer
optimizer = dict(type='SGD', lr=0.0001, momentum=0.9, weight_decay=0.0001)



# 下面是jsy加的
dataset_type = 'COCODataset'
classes = ("pedestrian" ,"bicycledriver", "motorbikedriver", "ignore",)
data = dict(
    samples_per_gpu=5,
    workers_per_gpu=2,
    train=dict(
        img_prefix='/data/composition/composition/train_dataset/nightowls_training',
        classes=classes,
        ann_file='/data/composition/composition/nightowls_training.json'),
    val=dict(
        img_prefix='/data/composition/composition/valid_dataset/nightowls_validation',
        classes=classes,
        ann_file='/data/composition/composition/nightowls_validation.json'),
    test=dict(
        img_prefix='/data/composition/composition/valid_dataset/nightowls_validation',
        classes=classes,
        ann_file='/data/composition/composition/nightowls_validation.json'))


model = dict(
    backbone=dict(
        init_cfg=dict(type='Pretrained', checkpoint='/data/composition/checkpoints/resnet50-19c8e357.pth')
    ),
    roi_head=dict(
        bbox_head=[
        dict(
            type='Shared2FCBBoxHead',
            num_classes=4,
            ),
        dict(
            type='Shared2FCBBoxHead',
            num_classes=4,
            ),
        dict(
            type='Shared2FCBBoxHead',
            num_classes=4,
        )
        ]
    )
)



runner = dict(type='EpochBasedRunner', max_epochs=50)